Previous |  Up |  Next

Article

Title: Fuzzy weighted average as a fuzzified aggregation operator and its properties (English)
Author: Pavlačka, Ondřej
Author: Pavlačková, Martina
Author: Hetfleiš, Vladislav
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 53
Issue: 1
Year: 2017
Pages: 137-160
Summary lang: English
.
Category: math
.
Summary: The weighted average is a well-known aggregation operator that is widely applied in various mathematical models. It possesses some important properties defined for aggregation operators, like monotonicity, continuity, idempotency, etc., that play an important role in practical applications. In the paper, we reveal whether and in which way such properties can be observed also for the fuzzy weighted average operator where the weights as well as the weighted values are expressed by noninteractive fuzzy numbers. The usefulness of the obtained results is discussed and illustrated by several numerical examples. (English)
Keyword: aggregation operator
Keyword: fuzzy weighted average
Keyword: fuzzy numbers
Keyword: fuzzy weights
MSC: 03E72
MSC: 68T37
idZBL: Zbl 06738599
idMR: MR3638561
DOI: 10.14736/kyb-2017-1-0137
.
Date available: 2017-04-03T10:52:39Z
Last updated: 2018-01-10
Stable URL: http://hdl.handle.net/10338.dmlcz/146713
.
Reference: [1] Baas, S., Kwakernaak, H.: Rating and ranking of multiple-aspect alternatives using fuzzy sets..Automatica 13 (1977), 47-58. MR 0439026, 10.1016/0005-1098(77)90008-5
Reference: [2] Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions: A Guide for Practitioners..Springer-Verlag, Berlin 2007.
Reference: [3] Calvo, T., Mayor, G., (eds.), R. Mesiar: Aggregation Operators: New Trends and Applications..Physica-Verlag, Heidelberg 2002. Zbl 0983.00020, MR 1936384, 10.1007/978-3-7908-1787-4
Reference: [4] Campos, L. M. De, Heute, J. F., Moral, S.: Probability intervals: a tool for uncertain reasoning..Int. J. Uncertainty, Fuzziness and Knowledge-Based Systems 2 (1994), 167-196. MR 1282406, 10.1142/s0218488594000146
Reference: [5] Dong, W. M., Wong, F. S.: Fuzzy weighted averages and implementation of the extension principle..Fuzzy Sets and Systems 21 (1987), 183-199. Zbl 0611.65100, MR 0871975, 10.1016/0165-0114(87)90163-1
Reference: [6] Dubois, D.: Fuzzy weighted averages and fuzzy convex sums: Authors response..Fuzzy Sets and Systems 213 (2013), 106-108. MR 3007014, 10.1016/j.fss.2012.09.003
Reference: [7] Dubois, D., Prade, H.: Additions of interactive fuzzy numbers..IEEE Trans. Automat. Control 26(1981), 4, 926-936. MR 0635852, 10.1109/tac.1981.1102744
Reference: [8] Fodor, J. C., Roubens, M.: Fuzzy Preference Modelling and Multicriteria Decision Support..Kluwer Academic Publishers, Dordrecht 1994. Zbl 0827.90002, 10.1007/978-94-017-1648-2_3
Reference: [9] Ghazinoory, S., Zadeh, A. E., Kheirkhah, A. S.: Application of fuzzy calculations for improving portfolio matrices..Inform. Sci. 180 (2010), 9, 1582-1590. 10.1016/j.ins.2010.01.012
Reference: [10] Grabisch, M., Marichal, J. L., Mesiar, R., Pap, E.: Aggregation Functions..Cambridge University Press, Cambridge 2009. Zbl 1206.68299, MR 2538324, 10.1017/cbo9781139644150
Reference: [11] Guh, Y.-Y., Hong, C. C., Wang, K. M., Lee, E. S.: Fuzzy weighted average: A max-min paired elimination method..Comp. Math. Appl. 32 (1996), 115-123. 10.1016/0898-1221(96)00171-x
Reference: [12] Guh, Y. Y., Hon, C. C., Lee, E. S.: Fuzzy weighted average: The linear programming approach via Charness and Coopers rule..Fuzzy Sets and Systems 117 (2001), 1, 157-160. MR 1891319, 10.1016/s0165-0114(98)00333-9
Reference: [13] Hung, K. C., Julian, P., Chien, T., Jin, W. T. H.: A decision support system for engineering design based on an enhanced fuzzy MCDM approach..Expert Systems Appl. 37 (1) (2010), 202-213. 10.1016/j.eswa.2009.04.069
Reference: [14] Chang, P. T., Hung, K. C.: Applying thefFuzzy-weighted-average approach to evaluate network security systems..Comp. Math. Appl. 49 (2005), 1797-1814. MR 2154685, 10.1016/j.camwa.2004.10.042
Reference: [15] Kao, C., Liu, S. T.: Fractional programming approach to fuzzy weighted average..Fuzzy Sets and Systems 120 (2001), 3, 435-444. Zbl 1103.90411, MR 1829262, 10.1016/s0165-0114(99)00137-2
Reference: [16] Kaufmann, A., Gupta, M. M.: Introduction to Fuzzy Arithmetic: Theory and Applications. (Second edition).Van Nostrand Reinhold, New York 1991. MR 1132439
Reference: [17] Klir, G. J., Pan, Y.: Constrained fuzzy arithmetic: Basic questions and some answers..Soft Computing 2 (1998), 100-108. 10.1007/s005000050038
Reference: [18] Klir, G. J., Yuan, B.: Fuzzy Sets and Fuzzy Logic: Theory and Applications..Prentice Hall, New Jersey, 1996. Zbl 0915.03001, MR 1443433
Reference: [19] Lin, C. H., Tan, B., Hsieh, P. J.: Application of the fuzzy weighted average in strategic portfolio management..Decision Sciences 36 (2005), 3, 489-511. 10.1111/j.1540-5414.2005.00081.x
Reference: [20] Liu, F., Mendel, J. M.: Aggregation using the fuzzy weighted average as computed by the Karnik-Mendel algorithms..IEEE Trans. Fuzzy Systems 16 (2008), 1, 1-12. 10.1109/tfuzz.2007.896229
Reference: [21] Liu, X., Mendel, J. M., Wu, D.: Analytical solution methods for the fuzzy weighted average..Inform. Sci. 187 (2012), 151-170. Zbl 1248.03072, MR 2869869, 10.1016/j.ins.2011.10.006
Reference: [22] Pavlačka, O., Talašová, J.: Application of the Fuzzy Weighted Average of Fuzzy Numbers in Decision Making Models..In: New Dimensions in Fuzzy Logic and Related Technologies. Vol II. (M. Štěpnička,, V. Novák, and U. Bodenhofer, eds.) Proc. 5th EUSFLAT Conference, Ostravská univerzita, Ostrava 2007, pp. 455-462.
Reference: [23] Pavlačka, O., Talašová, J.: Fuzzy vectors as a tool for modeling uncertain multidimensional quantities..Fuzzy Sets and Systems 161 (11) (2010), 1585-1603. Zbl 1186.90144, MR 2608263, 10.1016/j.fss.2009.12.008
Reference: [24] Pavlačka, O.: Modeling uncertain variables of the weighted average operation by fuzzy vectors..Inform. Sci. 181 (22) (2011), 4969-4992. Zbl 1241.68117, MR 2832874, 10.1016/j.ins.2011.06.022
Reference: [25] Pavlačka, O.: Note on the lack of equality between fuzzy weighted average and fuzzy convex sum..Fuzzy Sets and Systems 213 (2013), 102-105. Zbl 1291.91052, MR 3007013, 10.1016/j.fss.2012.08.003
Reference: [26] Ricci, R. G., Mesiar, R.: Multi-attribute aggregation operators..Fuzzy Sets and Systems 181 (2011), 1-13. Zbl 1236.68236, MR 2823722, 10.1016/j.fss.2011.06.008
Reference: [27] Sachs, T., Tiong, R. L. K.: Quantifying qualitative information on risks: development of the QQIR method..J. Construction Engrg. Management-Asce 135 (2009), 1, 56-71. 10.1061/(asce)0733-9364(2009)135:1(56)
Reference: [28] Talašová, J.: NEFRIT - Multicriteria Decision Making Based on Fuzzy Approach..Central Europ. J. Oper. Res. 8 (2000), 4, 297-319. Zbl 0981.90035, MR 1832867
Reference: [29] Wang, Y. M., Elhag, T. M. S.: Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment..Expert Systems Appl. 31 (2006), 2, 309-319. 10.1016/j.eswa.2005.09.040
Reference: [30] Wang, Y. M., Elhag, T. M. S.: On the normalization of interval and fuzzy weights..Fuzzy Sets and Systems 157 (2006), 2456-2471. Zbl 1171.68764, MR 2254175, 10.1016/j.fss.2006.06.008
Reference: [31] Wei, C. C., Chang, H. W.: A new approach for selecting portfolio of new product development projects..Expert Systems Appl. 38 (2011), 1, 429-434. 10.1016/j.eswa.2010.06.081
Reference: [32] Wu, W. Y., Lin, C. H., Kung, J. Y., Lin, C. T.: A new fuzzy TOPSIS for fuzzy MADM problems under group decisions..J. Intelligent and Fuzzy Systems 18 (2007), 2, 109-115. Zbl 1119.68193, MR 2327710
Reference: [33] Xu, Q., Ma, L., Nie, W. F., Li, P., Zhang, J. W., Sun, J. Z.: Adaptive fuzzy weighted average filter for synthesized image..In: Computational Science and Its Applications - ICCSA 2005, Part 3, Lecture Notes in Computer Science, vol. 3482, Springer-Verlag, Berlin 2005, pp. 292-298. 10.1007/11424857_32
.

Files

Files Size Format View
Kybernetika_53-2017-1_8.pdf 1.103Mb application/pdf View/Open
Back to standard record
Partner of
EuDML logo